Park et al. predicted T1 ccRCC aggressiveness with 85% accuracy (AUC: 0.796) by utilizing a model built on deep neural network algorithms and comprising data from FOXC2, PBRM, and BAP1 gene and protein expression [56]. The gene discussed is FOXC2; the disease is nonpapillary renal cell carcinoma.